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On Thursday, May 1, 2025, I hosted a space titled “Titles, Power, and Playing the Game” with my friends Skyler Payne and Giyu . Skylar is ex-Google, ex-LinkedIn, so he’s got those big corps under the belt; he even once politicked so hard, someone wrote a blind post about him. Giyu, meanwhile, just landed his first full-time job and is already climbing the ladder fast. But like anyone new to the corporate world, he’s been running into a few dilemmas along the way. That’s what sparked this audio space and the article you’re reading now.

Earlier in my career, whenever I heard “corporate politics,” I usually thought of greasy handshakes and backroom deals. Stuff I’d typically tune out because, frankly, I’d rather be building and learning. Very engineer-minded. I eventually realized that “corporate politics” wasn’t about manipulation, it was about learning to navigate the human network to actually get things done.

Giyu, who was hired with no previous full-time experiences but had a couple of years of consulting under his belt, was struggling with what job title to take. He got into an org that got him promoted within the first 3 days of his onboarding. He works directly with the CTO, and does a lot of heavy lifting: architecting, leading data, managing stakeholders across teams; but all at a newer company. He was hesitant to grab a big title like “Head of” or “Director” too early, worried it might mess with his path later. Title inflation is real, but also titles mean different things everywhere.

Skylar warned against jumping at a VP title too soon, especially in smaller shops where it might not have the real weight: “Titles signal your scope,” he said. Taking a VP title when you’re basically a super-strong tech lead can misrepresent things and cause headaches down the line when you talk to bigger companies. It can look like ego or make it hard to accept a title that fits the scope elsewhere.

But beyond the labels, Skyler pushed a deeper question: What kind of work do you actually want to be doing? Fire-fighting daily? Building medium-term? Long-term strategy? Hands-on coding vs. guiding others? Giyu felt strongest about medium-term building, maybe a 30/70 split coding vs. guiding.

Skyler broke down the usual paths:

Based on that, Skyler suggested “Staff+” made sense. It reflects the impact, partners with the CTO, but keeps future doors open. The key takeaway is to let the work you want to do drive the title, not the other way around. Focus on the what, the title follows the substance.

Skyler asked, “do you wanna do big things?” If so, you gotta get people on board and be seen. That alignment is politics. It’s about relationships, sure, but also visibility. You can’t just build cool stuff in the dark and expect things to happen.

He said it’s essentially about influence: selling your vision. Both he and Giyu stressed it’s not about being fake, but genuinely connecting and figuring out what makes people tick. Giyu admitted it felt weird at first, but seeing its value changed how he operated.

March 2024, reading through Hacker News Who Is Hiring Thread, I saw a job profile that fits me. I liked it so much that I reached out to the author that same night on LinkedIn (Co-founder & CTO). My profile based on previous employment alone would signal a misfit, but everything I do day-to-day in my own time tells a different story, this is my passion and I do it non-stop. Nevertheless, it was an uphill battle to convince the CTO to get on the phone with me. I basically wrote a 3-pages cover letter about my profile and how it matches their job description. He decided I should get a chance to go through their process, but ultimately they hired someone else who’s more experience with their stack. No hard feelings.

Last month I published From the Shadows to the Feed: Why I’m Finally Playing the Game . Since then, I have been honored with ~3.5k new followers. Superlinear growth is something I’m addicted to; I crave it in anything and everything I do in my life. Once I have the fundamentals down, I obsess over growth rates, getting better at a higher-than average pace is an absolute necessity to me.

Getting a job, however, in this market, was the opposite of superlinear. It was a death-by-a-thousand-cuts. I had already been dabbling with AI/LLMs for the past year or so, and I could foresee what was coming. I told my very supportive better half that I will not be applying for jobs because it’s a waste of time, and that given all indicators, I have to pivot and fully focus on AI, and invest heavily in it right now.

That’s how I came to build my AI Cluster . I sat down by the hours learning, experimenting, and stressing out about that bet I am taking on myself. I relaunched my website , started blogging, and started putting the time into making myself seen. Tweeting, trying to say hey, I am that kinda-famous user on r/LocalLLaMA .

I am here. I am good at what I do. I just don’t know how to get you to see it. Every now and then I would shamelessly, insert my AI server into replies when it’s relevant. I got invited to livestreams and accepted right away. I started hosting audio spaces on X/Twitter. I tweeted more and more frequently, engaged with people, made friends. I blogged some more. Wrote articles on X because the algo. Started my own YouTube channel. Livestreamed some stuff. Got invited to more live streams and more spaces… Finally, some superlinear growth.

But that’s not what this article is about.

When you’re playing the same game as everybody else, you’re pouring everything you’ve got into a game that was never designed to favor you. Unless you have an unfair advantage, you’re just gambling.

What’s my unfair advantage? What makes my profile hunted for? My focus immediately shifted to that after the experience I mentioned at the beginning of the article. I decided to stop playing the game with rules that aren’t meant to make me win. I’ll become the huntee.

In December last year, 3 months from my first blogpost and any of the activity I spoke of above, I cold emailed ~3-4 dozens of AI startups that were hiring on Hacker News. I pretty much wrote a paragraph about myself, attached links to a few of the things I have posted and built, and asked if they’d be interested in chatting.

I run an AI screenshot organizer locally from my PC. I don’t want to send my screenshots anywhere on the internet; my data is mine, and sending it to any proprietary model means I am giving away the rights to it. So, I have a local VLM pipeline that organizes all my screenshots, this pipeline was previously powered by my 14x RTX 3090s Basement AI Server and now is running directly from my PC with LMStudio SDK and occupying less than 6GB of GPU VRAM.

Recently LMStudio released their Python and Javascript SDKs . LMStudio is my go-to LLM desktop application , especially for models running directly on my PC and not AI Cluster. I have been intending to give their Python SDK a try with a small project, and the release of Gemma 3 new 4-bit quantization made me pull the trigger.

Given that Gemma 3 is a multimodal that accepts both image and text as input (4B, 12B, and 27B; 1B is text only), and the wild size (and performance) that the QAT quantization makes the model sit at, I decided to rewrite my screenshots organizer to run directly from my PC.

This article starts off slow, but it ramps up and gets way more interesting as we go. If you’d rather jump straight into the action, feel free to skip ahead to the Prerequisites section. And yep, this works on pretty much any image, not just screenshots.

My Screenshots Folder with 875 Screenshots

I hate a desktop littered with screenshots named Screenshot 2024-05-15 at 11.23.45 AM.png, Screen Shot 2024-05-16 at 9.01.12.png, or even worse, Untitled.png. The screenshots folder used to be where things went to die unless I use them right away. And then, sometimes, I find myself wondering about that one screenshot from 4 months ago!

When Qwen2-VL came out last year, I built an asynchronous pipeline that ran on my AI cluster to automatically rename, categorize, and organize my screenshots based on their content. Given my atypical use of my AI cluster, that pipeline didn’t run frequently, and I much preferred to run it from my PC directly; but I also didn’t want to replicate the complex software configuration on my PC. You can learn more about how I use my AI cluster in this blogpost . Again, LMStudio simplifies these processes on my PC, one-stop shop for ai models kind of thing, and I already have enough headaches to add more to it; so, ultimately, I ran this pipeline from my AI cluster every few weeks once the screenshots mess bothered me enough to go around remembering how to get the pipeline up and running.

In this post, we’ll build a practical screenshot organizer step-by-step, and in parallel we’ll get introduced to the core functionalities of the lmstudio-python library.

We’ll create a Python script that:

On Friday, April 11, 2025, I hosted a space titled “Is RAG Dead?” with my friend Skyler Payne . Skylar is ex-Google, ex-LinkedIn, currently building cutting-edge systems at Wicked Data and helping enterprises bring real AI solutions to production. This space has been on my mind for quite sometime now. There is this opinion floating around that “LLMs have 1M+ token context length now! We don’t need RAG anymore!” This isn’t just a bad take. It’s a misunderstanding of how actual AI systems are built. So, Skylar and I decided to host this space and talk it out together. What followed was one of the most technical, honest, no-bullshit convos I’ve had in a while about the actual role of RAG in 2025 and beyond.

If you don’t know me, I’m the guy with the 14x RTX 3090s Basement AI Server . I’ve been building and breaking AI systems for quite sometime now, I hold dual degrees in Computer Science and Data Science. I am also running a home lab that looks like it’s trying to outcompute a small startup (because it kind of is). I go deep on LLMs, inference optimization, agentic workflows, and all the weird edge cases that don’t make it into the marketing decks.

Let’s break it down.

Skyler opened by asking the obvious but important question: when people say “RAG,” what do they even mean?

Because half the time, it’s being reduced to just vector search. Chunk some PDFs, some cosine similarity, call it a day. But that’s not RAG.

Real RAG, at least the kind that works at scale, is more than just a search bar duct-taped to an LLM:

Also, definitions matter. If your definition stops at vector search and mine includes multi-hop planning and agents, we’re not debating. Understanding that nuance is key before you even ask whether RAG is “dead.” Because until we agree on the same definition, we’re just yelling at each other for the wrong thing.

The main argument against RAG is that LLMs can now eat entire PDFs. “Why retrieve when you can just feed it all in?” Doesn’t work.

Skyler walked us through what entreprises have on their hands:

For years, I stayed in the shadows. Not because I lacked ideas or ambition, but because I genuinely didn’t want to waste my time. Algorithm-centric timelines, packed with LARPers and algorithm-hackers, always felt like a cheap game; one where you could win by being louder, not necessarily better. And frankly, I didn’t care to play.

I’ve always believed in “don’t hate the player, hate the game,” and I still do. But here’s the thing: I’ve realized that ignoring the game doesn’t change the fact that it exists. While I was busy building in the dark, others were distributing. They were reaching the people I wanted to reach. They were building influence. They were making noise.

And so, I made a decision: if the game is distribution, I’ll play it. Not because I suddenly want clout, but because distribution matters. Ideas without distribution fade into the void. Execution without reach is just a hobby.

Besides my obsession with tech; LLMs, infrastructure, and all the wild experiments I run, I’ve become increasingly obsessed with networks over the past year. Not just the ones that run on fiber and copper, but the human ones. The networks that distribute ideas, opportunities, and influence.

I’m here for that distribution, my dude. I’m here to share insights, meet smart people, and ultimately show what I’m capable of. Because I’ve been building in silence for far too long. And while I don’t live for likes and retweets, I won’t lie, I enjoy the dopamine rush they bring. They act like signals: the network is listening.

I’ve actually made some genuinely good friends here. People I would have never met if I stayed lowkey. Some of the kindest, sharpest, and most driven people I’ve ever known.

So yeah, I’m playing the game now. I’m making noise. Just typing whatever’s on my mind. I’m building in the open. Because the game isn’t just about focus and execution; it’s about distribution. And when you have it all, you don’t just build products. You build waves.

Cheers.